From 9d0fe107b450273c968b07af26685e233a8ff4f0 Mon Sep 17 00:00:00 2001
From: Noelle <76960847+n0elleli@users.noreply.github.com>
Date: Fri, 13 Sep 2024 14:45:06 -0400
Subject: [PATCH] Delete FabricSamples/Image to Pipeline with AI/Step 5: Create
 the pipeline with Fabric REST APIs.py

---
 ...eate the pipeline with Fabric REST APIs.py | 123 ------------------
 1 file changed, 123 deletions(-)
 delete mode 100644 FabricSamples/Image to Pipeline with AI/Step 5: Create the pipeline with Fabric REST APIs.py

diff --git a/FabricSamples/Image to Pipeline with AI/Step 5: Create the pipeline with Fabric REST APIs.py b/FabricSamples/Image to Pipeline with AI/Step 5: Create the pipeline with Fabric REST APIs.py
deleted file mode 100644
index e524841f..00000000
--- a/FabricSamples/Image to Pipeline with AI/Step 5: Create the pipeline with Fabric REST APIs.py	
+++ /dev/null
@@ -1,123 +0,0 @@
-# Convert pipeline JSON to Fabric REST API request
-
-json_data = json.loads(pipeline_json)
-
-# Extract the activities from the JSON
-activities = json_data["properties"]["activities"]
-
-# Prepare the data pipeline JSON definition
-data = {}
-activities_list = []
-
-idx = 0
-
-# Name mapping used to track activity name found in image to dynamically generated name
-name_mapping = {}
-
-for activity in activities:
-    idx = idx + 1
-    activity_name = activity["type"].replace("Activity","")
-
-    objName = f"{activity_name}{idx}"
-
-    # store the name mapping so we can deal with dependency 
-    name_mapping[activity["name"]] = objName
-
-    if 'dependsOn' in activity: 
-        activity_dependent_list = activity["dependsOn"] 
-        
-        dependent_activity = ""
-        if ( len(activity_dependent_list) > 0 ):
-            dependent_activity = activity_dependent_list[0]["activity"]
-
-        match activity_name:
-            case "Copy":
-                activities_list.append({'name': objName, 'type': "Copy", 'dependsOn': [],
-                'typeProperties': { "source": { "datasetSettings": {} },
-                "sink": { "datasetSettings": {} } }})
-            case "Web":
-                activities_list.append({'name': objName, 'type': "Office365Outlook",
-                        "dependsOn": [
-                            {
-                                "activity":  name_mapping[dependent_activity] ,
-                                "dependencyConditions": [
-                                    "Succeeded"
-                                ]
-                            }
-                        ]
-                    }
-                )
-            case "ExecutePipeline":
-                activities_list.append({'name': "execute pipeline 1", 'type': "ExecutePipeline",
-                    "dependsOn": [
-                            {
-                                "activity":  name_mapping[dependent_activity] ,
-                                "dependencyConditions": [
-                                    "Succeeded"
-                                ]
-                            }
-                        ]
-                    }
-                )
-            case _:
-                continue
-    else:
-        # simple activities with no dependencies
-        match activity_name:
-            case "Copy":
-                activities_list.append({'name': objName, 'type': "Copy", 'dependsOn': [],
-                'typeProperties': { "source": { "datasetSettings": {} } , "sink": { "datasetSettings": {} } }})
-            case "SendEmail":
-                 activities_list.append({'name': "Send mail on success", 'type': "Office365Outlook"})
-            case "Web":
-                activities_list.append({'name': "Send mail on success", 'type': "Office365Outlook"})
-            case "ExecutePipeline":
-                activities_list.append({'name': "execute pipeline 1", 'type': "ExecutePipeline"})
-            case _:
-                print("NoOp")
-
-# Now that the activities_list is created, assign it to the activities tag in properties
-data['properties'] = { "activities": activities_list}
-
-# Convert data from dict to string, then Byte Literal, before doing a Base-64 encoding
-data_str = str(data).replace("'",'"')
-createPipeline_json = data_str.encode(encoding="utf-8")
-createPipeline_Json64 = base64.b64encode(createPipeline_json)
-
-# Create a new data pipeline in Fabric
-timestr = time.strftime("%Y%m%d-%H%M%S")
-pipelineName = f"Pipeline from image with AI-{timestr}"
-
-payload = {
-        "displayName": pipelineName,
-        "type": "DataPipeline",
-        "definition": {
-           "parts": [ 
-             { 
-              "path": "pipeline-content.json", 
-              "payload": createPipeline_Json64, 
-              "payloadType": "InlineBase64" 
-              }
-            ]
-        }
-}
-
-print(f"Creating pipeline: {pipelineName}")
-
-# Call the Fabric REST API to generate the pipeline
-client = fabric.FabricRestClient()
-workspaceId = fabric.get_workspace_id()
-try:
-    response = client.post(f"/v1/workspaces/{workspaceId}/items",json=payload)
-    if response.status_code != 201:
-        raise FabricHTTPException(response)
-except WorkspaceNotFoundException as e:
-    print("Workspace is not available or cannot be found.")
-except FabricHTTPException as e:
-    print(e)
-    print("Fabric HTTP Exception. Check that you have the correct Fabrric API endpoints.")
-
-response = client.get(f"/v1/workspaces/{workspaceId}/Datapipelines")
-df_items = pd.json_normalize(response.json()['value'])
-print("List of pipelines in the workspace:")
-df_items